本研究的目的是阐明肿瘤微环境 (TME) 与膀胱癌 (BLCA) 进展中的细胞多样性之间的关系，利用单细胞 RNA 测序 (scRNA-seq) 数据来识别潜在的预后生物标志物并构建预后模型我们分析了基因表达综合 (GEO) 数据库中正常和肿瘤膀胱细胞的 scRNA-seq 数据，以发现膀胱 TME 内的关键标记。该研究比较了正常膀胱细胞和肿瘤膀胱细胞中的基因表达，鉴定了差异表达的基因。随后使用癌症基因组图谱的患者随访数据评估这些基因的预后意义。使用最小绝对收缩和选择算子以及多元 Cox 回归分析构建预后模型，重点关注八个感兴趣的基因。该模型的预测性能还针对其他 GEO 数据集（GSE31684、GSE13507 和 GSE32894）进行了测试。该预后模型证明了对患者结果的可靠预测。通过基因集富集分析和免疫细胞浸润评估进行的验证支持了该模型的功效。单变量和多变量分析的结果表明，风险评分是一个独立的预后因素，风险比为 2.97（95% CI，2.28 至 3.9，P < .001）。在验证队列中，1年、2年和3年的AUC分别为0.74、0.74和0.72。我们的研究结果提出了具有预后潜力的生物标志物，为未来的体外验证和治疗探索奠定了基础。这有助于更深入地了解与膀胱 TME 相关的基因，并可能提高 BLCA 管理的预后精度。

The purpose of this study was to elucidate the relationship between the tumor microenvironment (TME) and cellular diversity in bladder cancer (BLCA) progression, leveraging single-cell RNA sequencing (scRNA-seq) data to identify potential prognostic biomarkers and construct a prognostic model for BLCA.We analyzed scRNA-seq data of normal and tumor bladder cells from the Gene Expression Omnibus (GEO) database to uncover crucial markers within the bladder TME. The study compared gene expression in normal versus tumor bladder cells, identifying differentially expressed genes. These genes were subsequently assessed for their prognostic significance using patient follow-up data from The Cancer Genome Atlas. Prognostic models were constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analyses, focusing on eight genes of interest. The predictive performance of the model was also tested against additional GEO data sets (GSE31684, GSE13507, and GSE32894).The prognostic model demonstrated reliable prediction of patient outcomes. Validation through gene set enrichment analysis and immune cell infiltration assessment supported the model's efficacy. The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001). In the validation cohort, the AUC at 1, 2, and 3 years is 0.74, 0.74, and 0.72, respectively.Our findings proposed biomarkers with prognostic potential, laying the groundwork for future in vitro validation and therapeutic exploration. This contributes to a deeper understanding of the genes associated with bladder TME and may improve prognostic precision in BLCA management.